SKKU IRIS Lab
SKKU IRIS Lab
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NeurIPS 2025 and West Coast Lab Visits
Visited UCSD, Samsung Research, and UCLA for invited talks and research collaboration on energy-efficient AI systems and large-scale AI optimization, alongside participating in NeurIPS 2025 with 5 accepted papers.
Dec 26, 2025
ICCAD 2025 and Europe Lab Visits
Participated in ICCAD 2025 in Munich and visited Politecnico di Torino, ETH Zurich, and IBM to discuss research collaboration on in-memory computing, neural architecture search, and efficient LLM serving.
Dec 23, 2025
Excellence Award at the SKKU Graduate Student Paper Competition (Researcher: Hyeonsu Bang)
IRIS Ph.D. student Hyeonsu Bang received the Excellence Award at the 2025 SKKU Graduate Student Paper Competition for a fault-tolerance scheme enabling reliable, efficient MLC ReRAM AI accelerators.
Dec 10, 2025
Carnegie Mellon University (CMU) Collaboration (Visiting Researcher: Jinju Kim)
Jinju Kim’s CMU visit advances machine unlearning for speech/audio privacy, including NeurIPS 2025 AI4Music work.
Oct 2, 2025
Duke University Collaboration (Visiting Researcher: Juhong Park)
Juhong Park’s Duke visit advances HW–SW co-optimization for LLM serving on DRAM-PIM/CIM NDP systems.
Oct 2, 2025
East Coast Lab Visits and Talks: Resource-Efficient AI via SW-HW Co-design
Presented our lab’s work on resource-efficient AI through SW–HW co-design at Duke, Cornell Tech, UIC, and UNC.
Sep 29, 2025
Undergraduate Researchers Lead ICCV 2025 Paper on Memory-Efficient Quantization
IRIS Lab undergraduate researchers Seokho Han and Seoyeon Yoon lead first-author paper at ICCV 2025, proposing MSQ for efficient on-device AI training.
Sep 15, 2025
Lab Photo Shoot
We conducted a lab photo shoot, capturing profile and group photos of the professor and lab members.
Sep 11, 2025
Prof. Yani Ioannou’s Seminar on ‘Training Structured Sparse Neural Networks’
Seminar by Prof. Yani Ioannou on SRigL and N:M structured sparsity with CPU/GPU speedups.
Sep 10, 2025
Prof. Bokyung Kim’s Seminar on ‘DPIMA: A DRAM-Based Processing-in-Memory Accelerator for Privacy-Preserving Machine Learning'
Rutgers’ Prof. Bokyung Kim presented DPIMA, a DRAM-based PIM accelerator for privacy-preserving ML (ISLPED 2025 Best Paper) at SKKU.
Sep 2, 2025
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